Contactless Respiration Monitoring Via Off-the-Shelf WiFi Devices

Liu, Xuefeng; Cao, Jiannong; Tang, Shaojie; Wen, Jiaqi; Guo, Peng

doi:10.1109/tmc.2015.2504935

Cited by 220 publications

(107 citation statements)

References 15 publications

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“…WiFi-based solutions are recently emerging as an alternative. For example, Liu et al [10] extract the personal respiratory data by use STFT(Short Time Fourier Transform) on the CSI (Channel State Information) derived from the wireless network card. To obtain a person's breathing information in different sleeping postures, they need to deploy two routers and three computers.…”

Section: Introductionmentioning

confidence: 99%

WiFi-Based Real-Time Breathing and Heart Rate Monitoring during Sleep

Zhang

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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Good quality sleep is essential for good health and sleep monitoring becomes a vital research topic. This paper provides a low cost, continuous and contactless WiFi-based vital signs (breathing and heart rate) monitoring method. In particular, we set up the antennas based on Fresnel diffraction model and signal propagation theory, which enhances the detection of weak breathing/heartbeat motion. We implement a prototype system using the off-shelf devices and a real-time processing system to monitor vital signs in real time. The experimental results indicate the accurate breathing rate and heart rate detection performance. To the best of our knowledge, this is the first work to use a pair of WiFi devices and omnidirectional antennas to achieve real-time individual breathing rate and heart rate monitoring in different sleeping postures.

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Section: Introductionmentioning

confidence: 99%

WiFi-Based Real-Time Breathing and Heart Rate Monitoring during Sleep

Zhang

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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“…Churkin and Anishchenko presented a new type of sensor for vital signs monitoring that utilizes mmWave radar (carrier wavelength is about 3 mm), Hence, they achieved significant noise immunity, sensitivity and accuracy [30] and also mmWave radar was discussed in [31]. Tracking Respiration at Different Sleeping Positions with off-the-shelf WiFi devices by collecting the fine-grained wireless channel state information (CSI) around a person was discussed by Lui et al [32] and similarly in [33].…”

Section: Related Workmentioning

confidence: 99%

Non-Contact Vital Signs Monitoring Through Visible Light Sensing

Abuella

Ekin

2020

IEEE Sensors J.

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In this paper, we present a wireless system for monitoring human vital signs like breathing and heartbeat via visible light sensing (VLS). Typical techniques for tracking heathcondition require body contact and most of these techniques are intrusive in nature. Body contact might irritate the patient's skin and he/she might feel uncomfortable while sensors are touching their body. However, in this method, we can estimate the breathing and heartbeat rates without any body contact using a photo-detector. Vitals monitoring using VLS make use of the idea that reflected light signal off the human body received at the photo-detector will be affected by the chest motion during heartbeats and breathing. We implemented the system using off-the-shelf photo-detector and a signal acquisition system and obtained the results for different people and in different scenarios. We found out that the accuracy of our system compared to FDA approved equipment to measure heartbeats and breathing rate is 94%. This system can be used in various domains and applications in medical facilities and in residential homes.A provisional patent (US#62/639,524) has been obtained for this work.

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“…Wi-Sleep [30] is the first sleep monitoring system that extracts rhythmical patterns caused by respiration from WiFi signals. The performance is further improved in [31] by considering the sleep postures and abnormal respiration patterns. Liu et al [29] have shown to track human heart rate by analyzing power spectral density (PSD) of CSI amplitude during sleep.…”

Section: Related Workmentioning

confidence: 99%

FarSense

Zeng

Xiong

et al. 2019

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

248

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The past few years have witnessed the great potential of exploiting channel state information retrieved from commodity WiFi devices for respiration monitoring. However, existing approaches only work when the target is close to the WiFi transceivers and the performance degrades significantly when the target is far away. On the other hand, most home environments only have one WiFi access point and it may not be located in the same room as the target. This sensing range constraint greatly limits the application of the proposed approaches in real life.This paper presents FarSense-the first real-time system that can reliably monitor human respiration when the target is far away from the WiFi transceiver pair. FarSense works well even when one of the transceivers is located in another room, moving a big step towards real-life deployment. We propose two novel schemes to achieve this goal: (1) Instead of applying the raw CSI readings of individual antenna for sensing, we employ the ratio of CSI readings from two antennas, whose noise is mostly canceled out by the division operation to significantly increase the sensing range; (2) The division operation further enables us to utilize the phase information which is not usable with one single antenna for sensing. The orthogonal amplitude and phase are elaborately combined to address the "blind spots" issue and further increase the sensing range. Extensive experiments show that FarSense is able to accurately monitor human respiration even when the target is 8 meters away from the transceiver pair, increasing the sensing range by more than 100%. 1 We believe this is the first system to enable through-wall respiration sensing with commodity WiFi devices and the proposed method could also benefit other sensing applications.CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing systems and tools; * This is the corresponding author 1 Different from radar with transmitter and receiver at the same location, the WiFi transmitter and receiver are separated physically. Here, the distance between a target and a transceiver pair is defined as the average distance from the target to the transmitter and the receiver.

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Contactless Respiration Monitoring Via Off-the-Shelf WiFi Devices

Cited by 220 publications

References 15 publications

WiFi-Based Real-Time Breathing and Heart Rate Monitoring during Sleep

WiFi-Based Real-Time Breathing and Heart Rate Monitoring during Sleep

Non-Contact Vital Signs Monitoring Through Visible Light Sensing

FarSense

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